@article {1299, title = {Using Open Source, Open Data, and Civic Technology to Address the COVID-19 Pandemic and Infodemic.}, journal = {Yearb Med Inform}, year = {2021}, month = {2021 Apr 21}, abstract = {

OBJECTIVES: The emerging COVID-19 pandemic has caused one of the world{\textquoteright}s worst health disasters compounded by social confusion with misinformation, the so-called "Infodemic". In this paper, we discuss how open technology approaches - including data sharing, visualization, and tooling - can address the COVID-19 pandemic and infodemic.

METHODS: In response to the call for participation in the 2020 International Medical Informatics Association (IMIA) Yearbook theme issue on Medical Informatics and the Pandemic, the IMIA Open Source Working Group surveyed recent works related to the use of Free/Libre/Open Source Software (FLOSS) for this pandemic.

RESULTS: FLOSS health care projects including GNU Health, OpenMRS, DHIS2, and others, have responded from the early phase of this pandemic. Data related to COVID-19 have been published from health organizations all over the world. Civic Technology, and the collaborative work of FLOSS and open data groups were considered to support collective intelligence on approaches to managing the pandemic.

CONCLUSION: FLOSS and open data have been effectively used to contribute to managing the COVID-19 pandemic, and open approaches to collaboration can improve trust in data.

}, issn = {2364-0502}, doi = {10.1055/s-0041-1726488}, author = {Kobayashi, Shinji and Falc{\'o}n, Luis and Fraser, Hamish and Braa, J{\o}rn and Amarakoon, Pamod and Marcelo, Alvin and Paton, Chris} } @article {1135, title = {Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals.}, journal = {BMJ Glob Health}, volume = {1}, year = {2016}, month = {2016 May 24}, pages = {e000028}, abstract = {

In many low income countries health information systems are poorly equipped to provide detailed information on hospital care and outcomes. Information is thus rarely used to support practice improvement. We describe efforts to tackle this challenge and to foster learning concerning collection and use of information. This could improve hospital services in Kenya. We are developing a Clinical Information Network, a collaboration spanning 14 hospitals, policy makers and researchers with the goal of improving information available on the quality of inpatient paediatric care across common childhood illnesses in Kenya. Standardised data from hospitals{\textquoteright} paediatric wards are collected using non-commercial and open source tools. We have implemented procedures for promoting data quality which are performed prior to a process of semi-automated analysis and routine report generation for hospitals in the network. In the first phase of the Clinical Information Network, we collected data on over 65 000 admission episodes. Despite clinicians{\textquoteright} initial unfamiliarity with routine performance reporting, we found that, as an initial focus, both engaging with each hospital and providing them information helped improve the quality of data and therefore reports. The process has involved mutual learning and building of trust in the data and should provide the basis for collaborative efforts to improve care, to understand patient outcome, and to evaluate interventions through shared learning. We have found that hospitals are willing to support the development of a clinically focused but geographically dispersed Clinical Information Network in a low-income setting. Such networks show considerable promise as platforms for collaborative efforts to improve care, to provide better information for decision making, and to enable locally relevant research.

}, issn = {2059-7908}, doi = {10.1136/bmjgh-2016-000028}, author = {Tuti, Timothy and Bitok, Michael and Malla, Lucas and Paton, Chris and Muinga, Naomi and Gathara, David and Gachau, Susan and Mbevi, George and Nyachiro, Wycliffe and Ogero, Morris and Julius, Thomas and Irimu, Grace and English, Mike} } @article {997, title = {Innovating to enhance clinical data management using non-commercial and open source solutions across a multi-center network supporting inpatient pediatric care and research in Kenya.}, journal = {J Am Med Inform Assoc}, year = {2015}, month = {2015 Jun 10}, abstract = {

OBJECTIVE: To share approaches and innovations adopted to deliver a relatively inexpensive clinical data management (CDM) framework within a low-income setting that aims to deliver quality pediatric data useful for supporting research, strengthening the information culture and informing improvement efforts in local clinical practice.

MATERIALS AND METHODS: The authors implemented a CDM framework to support a Clinical Information Network (CIN) using Research Electronic Data Capture (REDCap), a noncommercial software solution designed for rapid development and deployment of electronic data capture tools. It was used for collection of standardized data from case records of multiple hospitals{\textquoteright} pediatric wards. R, an open-source statistical language, was used for data quality enhancement, analysis, and report generation for the hospitals.

RESULTS: In the first year of CIN, the authors have developed innovative solutions to support the implementation of a secure, rapid pediatric data collection system spanning 14 hospital sites with stringent data quality checks. Data have been collated on over 37 000 admission episodes, with considerable improvement in clinical documentation of admissions observed. Using meta-programming techniques in R, coupled with branching logic, randomization, data lookup, and Application Programming Interface (API) features offered by REDCap, CDM tasks were configured and automated to ensure quality data was delivered for clinical improvement and research use.

CONCLUSION: A low-cost clinically focused but geographically dispersed quality CDM (Clinical Data Management) in a long-term, multi-site, and real world context can be achieved and sustained and challenges can be overcome through thoughtful design and implementation of open-source tools for handling data and supporting research.

}, issn = {1527-974X}, doi = {10.1093/jamia/ocv028}, author = {Tuti, Timothy and Bitok, Michael and Paton, Chris and Makone, Boniface and Malla, Lucas and Muinga, Naomi and Gathara, David and English, Mike} }